Academic literature on the topic 'SOFOG3D'

Abstract. In this study, we use a synergy of in situ and remote sensing measurements collected during the SOuthwest FOGs 3D experiment for processes study (SOFOG3D) field campaign in autumn and winter 2019–2020 to analyse the thermodynamic and turbulent processes related to fog formation, evolution, and dissipation across southwestern France. Based on a unique measurement dataset (synergy of cloud radar, microwave radiometer, wind lidar, and weather station data) combined with a fog conceptual model, an analysis of the four deepest fog episodes (two radiation fogs and two advection–radiation fogs) is conducted. The results show that radiation and advection–radiation fogs form under deep and thin temperature inversions, respectively. For both fog categories, the transition period from stable to adiabatic fog and the fog adiabatic phase are driven by vertical mixing associated with an increase in turbulence in the fog layer due to mechanical production (turbulence kinetic energy (TKE) up to 0.4 m2 s−2 and vertical velocity variance (σw2) up to 0.04 m2 s−2) generated by increasing wind and wind shear. Our study reveals that fog liquid water path, fog top height, temperature, radar reflectivity profiles, and fog adiabaticity derived from the conceptual model evolve in a consistent manner to clearly characterise this transition. The dissipation time is observed at night for the advection–radiation fog case studies and after sunrise for the radiation fog case studies. Night-time dissipation is driven by horizontal advection generating mechanical turbulence (TKE at least 0.3 m2 s−2 and σw2 larger than 0.04 m2 s−2). Daytime dissipation is linked to the combination of thermal and mechanical turbulence related to solar heating (near-surface sensible heat flux larger than 10 W m−2) and wind shear, respectively. This study demonstrates the added value of monitoring fog liquid water content and depth (combined with wind, turbulence, and temperature profiles) and diagnostics such as fog liquid water reservoir and adiabaticity to better explain the drivers of the fog life cycle.

Abstract. This study aims at introducing two conservative thermodynamic variables (moist-air entropy potential temperature and total water content) into a one-dimensional variational data assimilation system (1D-Var) to demonstrate their benefits for use in future operational assimilation schemes. This system is assessed using microwave brightness temperatures (TBs) from a ground-based radiometer installed during the SOFOG3D field campaign, dedicated to fog forecast improvement. An underlying objective is to ease the specification of background error covariance matrices that are highly dependent on weather conditions when using classical variables, making difficult the optimal retrievals of cloud and thermodynamic properties during fog conditions. Background error covariance matrices for these new conservative variables have thus been computed by an ensemble approach based on the French convective scale model AROME, for both all-weather and fog conditions. A first result shows that the use of these matrices for the new variables reduces some dependencies on the meteorological conditions (diurnal cycle, presence or not of clouds) compared to typical variables (temperature, specific humidity). Then, two 1D-Var experiments (classical vs. conservative variables) are evaluated over a full diurnal cycle characterized by a stratus-evolving radiative fog situation, using hourly TB. Results show, as expected, that TBs analysed by the 1D-Var are much closer to the observed ones than the background values for both variable choices. This is especially the case for channels sensitive to water vapour and liquid water. On the other hand, analysis increments in model space (water vapour, liquid water) show significant differences between the two sets of variables.

Abstract. This paper investigates the potential benefit of ground-based microwave radiometers (MWRs) to improve the initial state (analysis) of current numerical weather prediction (NWP) systems during fog conditions. To this end, temperature, humidity and liquid water path (LWP) retrievals have been performed by directly assimilating brightness temperatures using a one-dimensional variational technique (1D-Var). This study focuses on a fog-dedicated field-experiment performed over winter 2016–2017 in France. In situ measurements from a 120 m tower and radiosoundings are used to assess the improvement brought by the 1D-Var analysis to the background. A sensitivity study demonstrates the importance of the cross-correlations between temperature and specific humidity in the background-error-covariance matrix as well as the bias correction applied on MWR raw measurements. With the optimal 1D-Var configuration, root-mean-square errors smaller than 1.5 K (respectively 0.8 K) for temperature and 1 g kg−1 (respectively 0.5 g kg−1) for humidity are obtained up to 6 km altitude (respectively within the fog layer up to 250 m). A thin radiative fog case study has shown that the assimilation of MWR observations was able to correct large temperature errors of the AROME (Application of Research to Operations at MEsoscale) model as well as vertical and temporal errors observed in the fog life cycle. A statistical evaluation through the whole period has demonstrated that the largest impact when assimilating MWR observations is obtained on the temperature and LWP fields, while it is neutral to slightly positive for the specific humidity. Most of the temperature improvement is observed during false alarms when the AROME forecasts tend to significantly overestimate the temperature cooling. During missed fog profiles, 1D-Var analyses were found to increase the atmospheric stability within the first 100 m above the surface compared to the initial background profile. Concerning the LWP, the RMSE with respect to MWR statistical regressions is decreased from 101 g m−2 in the background to 27 g m−2 in the 1D-Var analysis. These encouraging results led to the deployment of eight MWRs during the international SOFOG3D (SOuth FOGs 3D experiment for fog processes study) experiment conducted by Météo-France.

In this position paper the Société Francophone d’OncoGériatrie (SOFOG; French-speaking oncogeriatric society), the Société Française de Pharmacie Oncologique (SFPO, French society for oncology pharmacy), the Groupe d’Investigateurs Nationaux pour l’Étude des Cancers de l’Ovaire et du sein (GINECO, National Investigators’ Group for Studies in Ovarian and Breast Cancer) and the Groupe Français de chirurgie Oncologique et Gynécologique (FRANCOGYN) propose a multi-disciplinary care planning of ovarian cancer in older patients. The treatment pathway is based on four successive decisional nodes (diagnosis, resectability assessment, operability assessment, adjuvant, and maintenance treatment decision) implying multidisciplinarity and adaptation of the treatment plan according to the patient’s geriatric covariates and her motivation towards treatment. Specific attention must be paid to geriatric intervention, supportive care and pharmaceutical conciliation. Studies are needed to prospectively evaluate the impact of geriatric vulnerability parameters at each step of the treatment agenda and the impact of geriatric interventions on patient outcomes.

Systematic molecular profiling and targeted therapy (TKI) have changed the face of Non-Small Cell Lung Cancer (NSCLC) treatment. However, there are no specific recommendations to address the prescription of TKI for older patients. A multidisciplinary task force from the French Society of Geriatric Oncology (SoFOG) and the French Society of Pulmonology/Oncology Group (SPLF/GOLF) conducted a systematic review from May 2010 to May 2021. Protocol registered in Prospero under number CRD42021224103. Three key questions were selected for older patients with NSCLC: (1) to whom TKI can be proposed, (2) for whom monotherapy should be favored, and (3) to whom a combination of TKI can be proposed. Among the 534 references isolated, 52 were included for the guidelines. The expert panel analysis concluded: (1) osimertinib 80 mg/day is recommended as a first-line treatment for older patients with the EGFR mutation; (2) full-dose first generation TKI, such as erlotinib or gefitinib, is feasible; (3) ALK and ROS1 rearrangement studies including older patients were too scarce to conclude on any definitive recommendations; and (4) given the actual data, TKI should be prescribed as monotherapy. Malnutrition, functional decline, and the number of comorbidities should be assessed primarily before TKI initiation.

Abstract. A new generation of cloud radars, with the ability to make observations close to the surface, presents the possibility of observing fog properties with better insight than was previously possible. The use of these instruments as part of an operational observation network could improve the prediction of fog events, something which is still a problem for even high-resolution numerical weather prediction models. However, the retrieval of liquid water content (LWC) profiles from radar reflectivity alone is an under-determined problem, something which ground-based microwave radiometer observations can help to constrain. In fact, microwave radiometers are not only sensitive to temperature and humidity profiles but are also known to be instruments of reference for the liquid water path. By providing the thermodynamic state of the atmosphere, to which the formation and evolution of fog events are highly sensitive, in addition to accurate liquid water path, which can be used to constrain the LWC retrieval from the cloud radar alone, combining microwave radiometers with cloud radars seems a natural next step to better understand and forecast fog events. To that end, a newly developed one-dimensional variational (1D-Var) algorithm designed for the retrieval of temperature, specific humidity and liquid water content profiles with both cloud radar and microwave radiometer (MWR) observations is presented in this study. The algorithm was developed to evaluate the capability of cloud radar and MWR to provide accurate LWC profiles in addition to temperature and humidity in view of assimilating the retrieved profiles into a 3D- and 4D-Var operational assimilation system. The algorithm is firstly tested on a synthetic dataset, which allows the evaluation of the developed algorithm in idealised conditions. This dataset was constructed by perturbing a high-resolution forecast dataset of fog and low-cloud cases by its expected errors. The algorithm is then tested with real data from the recent field campaign SOFOG-3D, carried out with the use of LWC measurements made from a tethered balloon platform. As expected, results from the synthetic dataset study were found to contain lower errors than those found from the retrievals on the dataset of real observations. It was found that LWC can be retrieved in idealised conditions with an uncertainty of less than 0.04 g m−3. With real data, as expected, retrievals with a good correlation (0.7) to in situ measurements were found but with a higher uncertainty than the synthetic dataset of around 0.06 g m−3 (41 %). This was reduced to 0.05 g m−3 (35 %) when an accurate droplet number concentration could be prescribed to the algorithm. A sensitivity study was conducted to discuss the impact of different settings used in the 1D-Var algorithm and the forward operator. Additionally, retrievals of LWC from a real fog event observed during the SOFOG-3D field campaign were found to significantly improve the operational background profiles of the AROME (Application of Research to Operations at MEsoscale) model, showing encouraging results for future improvement of the AROME model initial state during fog conditions.

Le brouillard est un phénomène difficile à prévoir en raison de sa faible extension verticale et de l’équilibre complexe des processus radiatifs, microphysiques, turbulents et dynamiques régissant son cycle de vie. Malgré une évolution croissante des moyens de mesure par télédétection, les propriétés microphysiques de la structure verticale du brouillard demeurent peu documentées. L’objectif de cette thèse est de caractériser l’évolution du profil vertical des propriétés microphysiques du brouillard et les principaux processus qui les pilotent durant son cycle de vie à partir d’un jeu de données unique.La campagne SOFOG3D s’est déroulée dans le sud-ouest de la France durant l’hiver 2019/2020, avec un dispositif instrumental inédit combinant mesures par télédétection (radiomètre micro-ondes et radar nuage) et mesures in situ au sol et sous ballon captif. Sur les trente épisodes de brouillard échantillonnés au super-site, majoritairement de type radiatif et radiatif-advectif, 18 épisodes ont été validés à partir des mesures de visibilité. L’analyse de leurs propriétés microphysiques au sol a montré de faibles concentrations de gouttelettes (médiane entre 20 et 40 cm-3) . De plus, les distributions dimensionnelles des gouttelettes, majoritairement bimodales, présentent des diamètres élevés, en particulier pour les épisodes radiatifs-advectifs.Les observations in situ sous ballon captif ont permis de mettre en évidence l’évolution conjointe des propriétés microphysiques et thermodynamiques sur la verticale, à partir de 140 profils verticaux collectés dans 8 épisodes de brouillards fins (épaisseur < 50 m) et 4 brouillards développés. Après la formation du brouillard, lorsqu’il est optiquement fin, i.e., transparent au rayonnement infrarouge, les conditions thermiques stables sont associées à un profil de contenu en eau liquide inversé, présentant des valeurs maximales au sol et décroissantes avec l’altitude. Après la transition en brouillard optiquement épais, lorsqu’elle se produit, des caractéristiques quasi-adiabatiques sont observées (profils d’eau liquide croissants avec l’altitude et de température légèrement instables). Ces observations in situ ont été confrontées à l’adiabaticité équivalente, dérivée du modèle conceptuel de Toledo et al. (2021), alimenté par des mesures par télédétection et d’observations en surface. La comparaison montre un accord satisfaisant entre les deux approches, sauf pour les brouillards les plus fins, où l’adiabaticité équivalente est sous-estimée par rapport à l’adiabaticité locale dérivée des mesures in situ par une méthode originale de régression.Les profils décroissants d’eau liquide dans les brouillards optiquement fins sont associés à une diminution du diamètre des gouttelettes avec l’altitude, une concentration faible et un mode de larges gouttelettes dominant près du sol. Pour les brouillards optiquement très fins (<20 m), le maximum de concentration est à l’inverse observé près du sol, traduisant une production de gouttelettes prépondérante en surface, consécutive au refroidissement nocturne. Pour les brouillards optiquement épais, contenu et concentration de gouttelettes augmentent avec l’altitude, soulignant le rôle de la croissance par condensation. De plus on met en évidence des zones de concentrations de petites gouttelettes plus élevées proche du sommet résultant probablement du processus d’activation des aérosols. Ces gouttelettes sédimentent ensuite vers les couches inférieures et grossissent par collision-coalescence, conduisant à la formation de larges gouttelettes (> 30 µm) au sol, associée à une distribution bimodale. Enfin, la distribution devient monomodale lorsque le brouillard se dissipe en stratus. Ces nouvelles connaissances sur l’évolution des propriétés microphysiques du brouillard au cours de son cycle de vie vont ainsi permettre d’évaluer et améliorer les schémas microphysiques des modèles numériques
Fog is a difficult phenomenon to forecast due to its limited vertical extent and the complex interactions between radiative, microphysical, turbulent and dynamic processes driving its life cycle. Despite increasing developments in remote sensing techniques, the microphysical properties of the fog vertical structure remain poorly documented. This thesis aims to characterize the evolution of the vertical profile of the fog microphysical properties and the main processes driving its life cycle, using a unique data set.The SOFOG3D campaign was conducted in southwest France during the winter of 2019/2020, with an innovative instrumental set-up, combining remote sensing measurements (microwave radiometer and cloud radar) and in situ measurements at ground level and under a tethered balloon. Of the 30 fog episodes sampled at the super-site, mainly radiative and radiative-advective fogs, 18 episodes were validated on the basis of visibility measurements. Analysis of their microphysical properties at ground level revealed low droplet concentrations (median between 20 and 40 cm-3). In addition, the droplet size distributions were mostly bimodal, with large diameters, particularly for radiative-advective episodes.In situ observations collected under a tethered balloon highlighted a combined evolution of the vertical microphysical and thermodynamic properties, based on 140 vertical profiles collected during 8 thin fog episodes (thickness < 50 m) and 4 thick fogs. After fog formation, when it is optically thin, i.e. transparent to infrared radiation, thermally stable conditions are associated with a reversed profile of liquid water content, with maximum values at ground level decreasing with height. After the transition to optically thick fog, when it occurs, quasi-adiabatic features are observed (liquid water profiles increasing with height and slightly unstable temperature profiles).These in situ observations were compared with the equivalent adiabaticity, derived from the conceptual model of Toledo et al (2021), based on remote sensing measurements and surface observations. The comparison shows satisfactory agreement between the two approaches, with the exception of very thin fogs, where the equivalent adiabaticity is underestimated compared with local adiabaticity, derived from in situ measurements, using an original regression method.Decreasing liquid water profiles in optically thin fogs are associated with decreasing droplet diameters with height, low concentrations and a dominant mode of large droplets near the ground. For optically very thin fogs (<20 m), maximum concentrations are observed near the ground, indicating a predominant droplet production at the surface, following radiative cooling. In optically thick fogs, droplet content and concentration increase with height, illustrating the importance of condensation growth. In addition, we find areas of higher concentration of small droplets near the top, resulting probably from aerosol activation. These droplets then settle towards the lower layers and grow by collision-coalescence, leading to the formation of large droplets (> 30 µm) at ground level, associated with a bimodal distribution. Finally, the distribution becomes monomodal when the fog dissipates into stratus. This new knowledge of the evolution of the fog microphysical properties during its life cycle make it possible to evaluate and improve the microphysical schemes in numerical models